Merging FNGS

BNU1

Sanity Check

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_merge/BNU1/roi_timeseries/desikan-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 3
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

## Warning: package 'reshape2' was built under R version 3.3.3

## Warning: package 'ggplot2' was built under R version 3.3.3

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(cor(ts1), title=title, legend="corr"))

Non Ranking

Spectral Approach

Raw Amplitude Spectrum

  tr = 2.5
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- data.frame(dataset='BNU1', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d))

DC1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_merge/DC1/roi_timeseries/desikan-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 3
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(cor(ts1), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 2.5
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='DC1', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

NKI1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_merge/NKI1/roi_timeseries/desikan-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 4
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(cor(ts1), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 1.4
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='NKI1', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

LMU1

Non Ranking

  require(Discriminability)
  inpath <- 'C:/Users/ebrid/Documents/R/fngs_merge/LMU1/roi_timeseries/desikan-2mm/'
  tsnames <- list.files(inpath, pattern="\\.rds", full.names=TRUE)
  scan_pos = 4
  tsobj <- open_timeseries(tsnames, sub_pos=scan_pos, exclude = TRUE)

## [1] "opening timeseries..."

  signal <- tsobj[[1]]
  ids <- tsobj[[3]]

Sanity Check

Timeseries

  ts1 = signal[[1]]
  title = paste('Timeseries plot for subject', ids[1])
  print(plot_timeseries(ts1, title=title))

### Correlation Matrix

  title = paste('Correlation plot for subject', ids[1])
  print(plot_square(cor(ts1), title=title, legend="corr"))

Spectral Approach

Raw Amplitude Spectrum

  tr = 2.5
  lc = 0.01
  amp <- freq_discr(signal, ids, tr, lc, spec='amp', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(amp$combinedplot)

## NULL

Raw Power Spectrum

  pow <- freq_discr(signal, ids, tr, lc, spec='pow', rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(pow$combinedplot)

## NULL

Standard Discriminability Approach

Raw Correaltion Graphs

  td <- time_discr(signal, ids, rank=FALSE)

## [1] "computing hellinger distances and densities..."

  print(td$combinedplot)

## NULL

Ranking

Spectral Approach

Ranked Amplitude Spectrum

  ampr <- freq_discr(signal, ids, tr, lc, spec='amp', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(ampr$combinedplot)

## NULL

Ranked Power Spectrum

  powr <- freq_discr(signal, ids, tr, lc, spec='pow', rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(powr$combinedplot)

## NULL

Standard Discriminability Approach

Ranked Correlation Graphs

  tdr <- time_discr(signal, ids, rank=TRUE)

## [1] "computing hellinger distances and densities..."

  print(tdr$combinedplot)

## NULL

  collection <- rbind(collection, data.frame(dataset='LMU1', postprocessing=c('amp', 'power', 'corr', 'ramped', 'rpower', 'rcorr'),
                           discr=c(amp$d, pow$d, td$d, ampr$d, powr$d, tdr$d)))

  summaryfig <- ggplot(collection, aes(x=postprocessing, y=discr, color=factor(dataset), shape=factor(dataset))) +
    geom_point(size=2) +
    ggtitle('Comparing Discriminability over 4 reference datasets using different postprocessing techniques')
  print(summaryfig)

  summaryfig <- ggplot(collection, aes(x=postprocessing, y=discr, fill=factor(postprocessing))) +
    geom_violin() +
    geom_boxplot(width=0.1) +
    ggtitle('Comparing Discriminability over 4 reference datasets using different postprocessing techniques')
  print(summaryfig)